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Using The Lisa Genetic Cluster
European Neuropsychopharmacology (2019) 29, S713–S776
www.elsevier.com/locate/euroneuro
Abstracts of the XXV World Congress of Psychiatric Genetics (WCPG): Symposia Abstracts
Friday, October 13, 2017 8:00 a.m. - 3:45 p.m. Education Day
USING THE LISA GENETIC CLUSTER
PGC DATA ACCESS COMMITTEE: METHODS TO ACCESS PGC DATA
VU Amsterdam
Danielle Posthuma (Chair)
Abstract
VU Amsterdam Overall Abstract In 2015, the PGC has set-up the Data Access Committee who oversees access to summary statistics generated by PGCworkgroups as well as access to cleaned genotype data that are part of PGC. The DAC has created clear disease-specific guidelines for data access, a transparent structure on the LISA cluster computer for file access, and tracks data access approvals. The DAC consists of representatives from every PGC workgroup who are responsible for checking data access restrictions. All data access requests are received via the online DAC portal. The DAC aims to facilitate secondary analyses on PGC datasets. In this symposium, we explain the role of the DAC, provide an overview of the kind of data the DAC oversees, explain how to gain access and analyze the data and provide an example of a secondary analyses using the DAC.
Danielle Posthuma
Background: Through the PGC-DAC portal PGC users obtain access to PGC-related phenotypic and genetic data. All PGC data is stored on the Dutch Genetic Cluster Computer, called LISA. PGC users sign a contract in which they state they will not remove the data to which they have access to from the LISA cluster. All analyses with the data thus have to be carried out on the LISA cluster. Methods: The session will show how to run analyses on the LISA cluster, including how to write jobs efficiently, how to submit jobs, how to manage jobs, and how to store data efficiently. It will also explain the rationale behind the job scheduling and priority system. Results: N/A (education day) Conclusions: The aim of this session is to inform PGC members how to handle and analyze the PGC data on the LISA cluster in an efficient and responsible way.
Disclosure
Disclosure
Nothing to disclose.
Nothing to disclose.
http://dx.doi.org/10.1016/j.euroneuro.2017.06.018
http://dx.doi.org/10.1016/j.euroneuro.2017.06.019
0924-977X
www.elsevier.com/locate/euroneuro
Abstracts of the XXV World Congress of Psychiatric Genetics (WCPG): Symposia Abstracts
Friday, October 13, 2017 8:00 a.m. - 3:45 p.m. Education Day
USING THE LISA GENETIC CLUSTER
PGC DATA ACCESS COMMITTEE: METHODS TO ACCESS PGC DATA
VU Amsterdam
Danielle Posthuma (Chair)
Abstract
VU Amsterdam Overall Abstract In 2015, the PGC has set-up the Data Access Committee who oversees access to summary statistics generated by PGCworkgroups as well as access to cleaned genotype data that are part of PGC. The DAC has created clear disease-specific guidelines for data access, a transparent structure on the LISA cluster computer for file access, and tracks data access approvals. The DAC consists of representatives from every PGC workgroup who are responsible for checking data access restrictions. All data access requests are received via the online DAC portal. The DAC aims to facilitate secondary analyses on PGC datasets. In this symposium, we explain the role of the DAC, provide an overview of the kind of data the DAC oversees, explain how to gain access and analyze the data and provide an example of a secondary analyses using the DAC.
Danielle Posthuma
Background: Through the PGC-DAC portal PGC users obtain access to PGC-related phenotypic and genetic data. All PGC data is stored on the Dutch Genetic Cluster Computer, called LISA. PGC users sign a contract in which they state they will not remove the data to which they have access to from the LISA cluster. All analyses with the data thus have to be carried out on the LISA cluster. Methods: The session will show how to run analyses on the LISA cluster, including how to write jobs efficiently, how to submit jobs, how to manage jobs, and how to store data efficiently. It will also explain the rationale behind the job scheduling and priority system. Results: N/A (education day) Conclusions: The aim of this session is to inform PGC members how to handle and analyze the PGC data on the LISA cluster in an efficient and responsible way.
Disclosure
Disclosure
Nothing to disclose.
Nothing to disclose.
http://dx.doi.org/10.1016/j.euroneuro.2017.06.018
http://dx.doi.org/10.1016/j.euroneuro.2017.06.019
0924-977X